这篇文章主要介绍了c#实现识别图片上的验证码数字的方法，本文给大家汇总了2种方法，有需要的小伙伴可以参考下。
public void imgdo(Bitmap img) { //去色 Bitmap btp = img; Color c = new Color(); int rr, gg, bb; for (int i = 0; i < btp.Width; i++) { for (int j = 0; j < btp.Height; j++) { //取图片当前的像素点 c = btp.GetPixel(i, j); rr = c.R; gg = c.G; bb = c.B; //改变颜色 if (rr == 102 && gg == 0 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } if (rr == 153 && gg == 0 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } if (rr == 153 && gg == 0 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } if (rr == 153 && gg == 43 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } if (rr == 255 && gg == 255 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } if (rr == 255 && gg == 255 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255)); } } } btp.Save("d:\\去除相关颜色.png"); pictureBox2.Image = Image.FromFile("d:\\去除相关颜色.png"); //灰度 Bitmap bmphd = btp; for (int i = 0; i < bmphd.Width; i++) { for (int j = 0; j < bmphd.Height; j++) { //取图片当前的像素点 var color = bmphd.GetPixel(i, j); var gray = (int)(color.R * 0.001 + color.G * 0.700 + color.B * 0.250); //重新设置当前的像素点 bmphd.SetPixel(i, j, Color.FromArgb(gray, gray, gray)); } } bmphd.Save("d:\\灰度.png"); pictureBox27.Image = Image.FromFile("d:\\灰度.png"); //二值化 Bitmap erzhi = bmphd; Bitmap orcbmp; int nn = 3; int w = erzhi.Width; int h = erzhi.Height; BitmapData data = erzhi.LockBits(new Rectangle(0, 0, w, h), ImageLockMode.ReadOnly, PixelFormat.Format24bppRgb); unsafe { byte* p = (byte*)data.Scan0; byte[,] vSource = new byte[w, h]; int offset = data.Stride - w * nn; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { vSource[x, y] = (byte)(((int)p[0] + (int)p[1] + (int)p[2]) / 3); p += nn; } p += offset; } erzhi.UnlockBits(data); Bitmap bmpDest = new Bitmap(w, h, PixelFormat.Format24bppRgb); BitmapData dataDest = bmpDest.LockBits(new Rectangle(0, 0, w, h), ImageLockMode.WriteOnly, PixelFormat.Format24bppRgb); p = (byte*)dataDest.Scan0; offset = dataDest.Stride - w * nn; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { p[0] = p[1] = p[2] = (int)vSource[x, y] > 161 ? (byte)255 : (byte)0; //p[0] = p[1] = p[2] = (int)GetAverageColor(vSource, x, y, w, h) > 50 ? (byte)255 : (byte)0; p += nn; } p += offset; } bmpDest.UnlockBits(dataDest); orcbmp = bmpDest; orcbmp.Save("d:\\二值化.png"); pictureBox29.Image = Image.FromFile("d:\\二值化.png"); } //OCR的值 if (orcbmp != null) { string result = Ocr(orcbmp); label32.Text = result.Replace("\n", "\r\n").Replace(" ", ""); } }
C#识别验证码图片通用类
using System;using System.Collections.Generic;using System.Text;using System.Collections;using System.Drawing;using System.Drawing.Imaging;using System.Runtime.InteropServices; namespace BallotAiying2{ class UnCodebase { public Bitmap bmpobj; public UnCodebase(Bitmap pic) { bmpobj = new Bitmap(pic); //转换为Format32bppRgb } /// /// 根据RGB，计算灰度值 /// /// Color值 /// 灰度值，整型 private int GetGrayNumColor(System.Drawing.Color posClr) { return (posClr.R * 19595 + posClr.G * 38469 + posClr.B * 7472) >> 16; } /// /// 灰度转换,逐点方式 /// public void GrayByPixels() { for (int i = 0; i < bmpobj.Height; i++) { for (int j = 0; j < bmpobj.Width; j++) { int tmpValue = GetGrayNumColor(bmpobj.GetPixel(j, i)); bmpobj.SetPixel(j, i, Color.FromArgb(tmpValue, tmpValue, tmpValue)); } } } /// /// 去图形边框 /// /// public void ClearPicBorder(int borderWidth) { for (int i = 0; i < bmpobj.Height; i++) { for (int j = 0; j < bmpobj.Width; j++) { if (i < borderWidth || j < borderWidth || j > bmpobj.Width - 1 - borderWidth || i > bmpobj.Height - 1 - borderWidth) bmpobj.SetPixel(j, i, Color.FromArgb(255, 255, 255)); } } } /// /// 灰度转换,逐行方式 /// public void GrayByLine() { Rectangle rec = new Rectangle(0, 0, bmpobj.Width, bmpobj.Height); BitmapData bmpData = bmpobj.LockBits(rec, ImageLockMode.ReadWrite, bmpobj.PixelFormat);// PixelFormat.Format32bppPArgb); // bmpData.PixelFormat = PixelFormat.Format24bppRgb; IntPtr scan0 = bmpData.Scan0; int len = bmpobj.Width * bmpobj.Height; int[] pixels = new int[len]; Marshal.Copy(scan0, pixels, 0, len); //对图片进行处理 int GrayValue = 0; for (int i = 0; i < len; i++) { GrayValue = GetGrayNumColor(Color.FromArgb(pixels)); pixels = (byte)(Color.FromArgb(GrayValue, GrayValue, GrayValue)).ToArgb(); //Color转byte } bmpobj.UnlockBits(bmpData); } /// /// 得到有效图形并调整为可平均分割的大小 /// /// 灰度背景分界值 /// 有效字符数 /// /// 得到有效图形,图形为类变量 /// /// 灰度背景分界值 /// 有效字符数 /// /// 得到有效图形,图形由外面传入 /// /// 灰度背景分界值 /// 有效字符数 /// /// 平均分割图片 /// /// 水平上分割数 /// 垂直上分割数 /// 分割好的图片数组 public Bitmap [] GetSplitPics(int RowNum,int ColNum) { if (RowNum == 0 || ColNum == 0) return null; int singW = bmpobj.Width / RowNum; int singH = bmpobj.Height / ColNum; Bitmap [] PicArray=new Bitmap[RowNum*ColNum]; Rectangle cloneRect; for (int i = 0; i < ColNum; i++) //找有效区 { for (int j = 0; j < RowNum; j++) { cloneRect = new Rectangle(j*singW, i*singH, singW , singH); PicArray[i*RowNum+j]=bmpobj.Clone(cloneRect, bmpobj.PixelFormat);//复制小块图 } } return PicArray; } /// /// 返回灰度图片的点阵描述字串，1表示灰点，0表示背景 /// /// 灰度图 /// 背前景灰色界限 ///
以上2则都是使用C#实现的orc识别的代码，希望对大家学习C#有所帮助。
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